Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 122,100
2 South Dakota 113,639
3 Wisconsin 90,382
4 Iowa 90,240
5 Utah 88,420
6 Nebraska 87,512
7 Tennessee 86,886
8 Rhode Island 83,020
9 Idaho 79,777
10 Kansas 79,068
11 Indiana 78,585
12 Wyoming 77,536
13 Illinois 77,503
14 Arkansas 77,365
15 Montana 77,079
16 Oklahoma 76,844
17 Arizona 76,439
18 Alabama 75,855
19 Nevada 75,278
20 Mississippi 74,613
21 Minnesota 74,579
22 New Mexico 69,816
23 Missouri 69,489
24 Louisiana 69,062
25 Alaska 65,404
26 Florida 63,574
27 Georgia 62,887
28 South Carolina 62,475
29 Texas 62,424
30 Kentucky 62,331
31 Ohio 61,722
32 California 61,597
33 Delaware 61,086
34 Colorado 59,473
35 Massachusetts 56,244
36 New Jersey 55,624
37 North Carolina 53,895
38 Michigan 53,674
39 Connecticut 53,325
40 New York 52,646
41 Pennsylvania 52,039
42 West Virginia 50,809
43 Maryland 47,221
44 Virginia 42,617
45 District of Columbia 42,173
46 Puerto Rico 35,001
47 New Hampshire 34,161
48 Washington 33,954
49 Oregon 27,916
50 Maine 19,038
51 Hawaii 15,550
52 Vermont 12,489

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 Arizona 1,490
2 Oklahoma 1,106
3 West Virginia 1,064
4 California 1,063
5 Tennessee 1,014
6 Arkansas 920
7 South Carolina 916
8 New York 773
9 North Carolina 768
10 Georgia 742
11 Alabama 727
12 Nevada 724
13 Indiana 722
14 Kentucky 719
15 Utah 713
16 Mississippi 700
17 Delaware 694
18 Florida 653
19 Massachusetts 603
20 Ohio 601
21 New Hampshire 593
22 Kansas 560
23 New Mexico 555
24 Virginia 553
25 New Jersey 550
26 Pennsylvania 524
27 South Dakota 515
28 Alaska 503
29 Maryland 477
30 Texas 435
31 Illinois 427
32 Missouri 426
33 Louisiana 414
34 Connecticut 412
35 Colorado 400
36 Nebraska 371
37 District of Columbia 368
38 Maine 344
39 Wisconsin 332
40 Washington 327
41 Iowa 317
42 Minnesota 309
43 Oregon 301
44 Michigan 294
45 Wyoming 268
46 North Dakota 238
47 Idaho 220
48 Montana 212
49 Vermont 203
50 Puerto Rico 196
51 Hawaii 131
52 Rhode Island 0

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 2,162
2 New York 1,953
3 Massachusetts 1,829
4 North Dakota 1,728
5 Connecticut 1,710
6 South Dakota 1,710
7 Rhode Island 1,677
8 Mississippi 1,636
9 Louisiana 1,621
10 Illinois 1,445
11 Michigan 1,331
12 Pennsylvania 1,275
13 Indiana 1,258
14 Iowa 1,250
15 Arizona 1,244
16 Arkansas 1,242
17 New Mexico 1,217
18 District of Columbia 1,125
19 South Carolina 1,062
20 Nevada 1,037
21 Florida 1,023
22 Tennessee 1,019
23 Georgia 999
24 Alabama 993
25 Maryland 991
26 Kansas 988
27 Texas 984
28 Minnesota 973
29 Missouri 965
30 Delaware 955
31 Montana 909
32 Wisconsin 904
33 Nebraska 876
34 Colorado 867
35 Idaho 811
36 Ohio 776
37 West Virginia 767
38 Wyoming 756
39 California 674
40 Kentucky 674
41 North Carolina 663
42 Oklahoma 643
43 Virginia 600
44 New Hampshire 573
45 Puerto Rico 483
46 Washington 462
47 Utah 405
48 Oregon 358
49 Alaska 282
50 Maine 267
51 Vermont 224
52 Hawaii 202

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 Kansas 15
2 New Mexico 11
3 South Carolina 11
4 Indiana 10
5 Connecticut 9
6 Illinois 9
7 Massachusetts 9
8 Michigan 9
9 Mississippi 9
10 South Dakota 9
11 Arizona 8
12 Arkansas 8
13 New York 7
14 North Dakota 7
15 Pennsylvania 7
16 West Virginia 7
17 Colorado 6
18 Minnesota 6
19 Nevada 6
20 New Jersey 6
21 California 5
22 Iowa 5
23 Maryland 5
24 New Hampshire 5
25 Tennessee 5
26 Alaska 4
27 Florida 4
28 Kentucky 4
29 North Carolina 4
30 Oklahoma 4
31 Puerto Rico 4
32 Texas 4
33 Alabama 3
34 District of Columbia 3
35 Louisiana 3
36 Montana 3
37 Ohio 3
38 Utah 3
39 Virginia 3
40 Idaho 2
41 Maine 2
42 Missouri 2
43 Nebraska 2
44 Vermont 2
45 Delaware 1
46 Oregon 1
47 Wisconsin 1
48 Georgia 0
49 Hawaii 0
50 Rhode Island 0
51 Washington 0
52 Wyoming 0

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Crowley Colorado 273,882 1 99
Dewey South Dakota 221,317 2 99
Norton Kansas 220,854 3 99
Lincoln Arkansas 218,673 4 99
Bon Homme South Dakota 214,027 5 99
Davidson Tennessee 102,810 284 90
Richland South Carolina 65,247 1591 49
York South Carolina 57,474 1984 36
Orange California 53,784 2146 31
Pierce Washington 31,554 2833 9

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Gove Kansas 7,587 1 99
Jerauld South Dakota 7,452 2 99
Dickey North Dakota 6,568 3 99
Gregory South Dakota 6,213 4 99
Iron Wisconsin 6,154 5 99
Davidson Tennessee 830 1825 41
Richland South Carolina 825 1835 41
York South Carolina 662 2116 32
Orange California 599 2222 29
Pierce Washington 385 2599 17

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons